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Modern
civilization has become so developed and sophisticated that to
survive you have to be competitive. By comparing and contrasting you
can identify your position as either a winner or a loser, as either
better, worse, or somewhere in the middle. To compete with other
trends, we need a vast amount of data. A huge collection of data from
various sources not only fills the information gap, but also gives us
an apparent feeling of being able to control the world, as well as an
awareness and knowledge about our environment.
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Data
is the name given to “raw material”, i.e. anything that is or can be processed
mentally or by any computing machine.
This "processability", that is, the possibility of using
data further, is one of the main purposes of data collection. Thus, by definition, data are plain facts or figures collected together for analysis, reference and interpretation.
Data
can be used not only in an abstract context, but also in all areas of life since huge amounts of information are assimilated and then analyzed for development, market analysis, financial predictions, insights into human behavior and reactions, etc.
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Although
the words data
and informationseem
very much alike, there are lots of differences between these two. As already mentioned, data are plain facts, but when these facts are processed, organized, structured or presented in a given context so as to make them useful, they become information.
Thus, it is not enough to simply collect data, as without processing,
they are fairly useless. It is analysis and interpretation which
makes them meaningful. Information is data that has been converted into a more useful or intelligible form for utilization. It may be noted that information may be further processed and/or manipulated to form knowledge,
which is defined as information containing wisdom.
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The
difference between data and information has now been defined, so let us consider data
presentation.
Effective
data presentation is
nothing more than the provision of information in a way that it can be understood, sometimes remembered, and most importantly, analyzed, processed and interpreted by the audience.
The
presentation of theories, hypotheses or theses seems relatively easy compared with presenting numbers, statistics and hard data. How can we make numbers, statistics and hard data interesting or even surprising for our audience? How can we inspire our audience to analyze the data and, consequently, encourage them to formulate new theories contributing to the development of knowledge?
Dealing
with data effectively
Ingredients
for cooking the final “dish”:
data
collected, context, computer, logical and analytical thinking,
purpose of the presentation (audience), and patience.
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Data
presentation needs to have a precise purpose, therefore it should be related to a specific context and prepared for a specific audience. Providing a context helps the audience visualize and understand the numbers.
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Collected
data should be processed in a way that is comprehensible to an
audience.
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The
design of visuals ought to be readable and clear. Ensure your
audience understand at a glance what your data represent, but at the same time keep them sufficiently vague so that they pay attention to your speech for more information.
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Logical
and analytical thinking should be the starting point of data
interpretation.
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Keep
it simple – when it comes to making data digestible, simplicity, neat positioning and clever formatting are key.
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Use
text wisely and sparingly. Text plays a vital role in data
presentation so it should be used strategically. Keep text to a
minimum and as a supporting element.
